Models to predict the public health impact of vaccine resistance: A systematic review

Abstract

Pathogen evolution is a potential threat to the long-term benefits provided by public health vaccination campaigns. Mathematical modeling can be a powerful tool to examine the forces responsible for the development of vaccine resistance and to predict its public health implications. We conducted a systematic review of existing literature to understand the construction and application of vaccine resistance models. We identified 26 studies that modeled the public health impact of vaccine resistance for 12 different pathogens. Most models predicted that vaccines would reduce overall disease burden in spite of evolution of vaccine resistance. Relatively few pathogens and populations for which vaccine resistance may be problematic were covered in the reviewed studies, with low- and middle-income countries particularly under-represented. We discuss the key components of model design, as well as patterns of model predictions.

Keywords: Mathematical modeling; Vaccine resistance.

Figure 1.

PRISMA flow diagram of study screening process Study exclusion rationale: “no VR” = study did not address vaccine resistance “no model” = study did not use a mathematical model “no PH” = study did not model public health outcomes “analytical” = study was mainly theoretical/conceptual

Figure 2.

Tree maps of the proportion of studies (#) by pathogen, type of resistance, and region studied, as well as model structure